En-Route Planning of Multi-Destination Public-Transport Trips Using Smartphones

Abstract

Public transport travelers require well-integrated, real-time information systems to use a network. The objective of this study was twofold: (1) to develop a model to determine the effect of personalized information provision through smartphones on user ability to plan multi-destination trips, and (2) to understand user perception of riding public transport aided by real-time, multi-destination trip-planning smartphone applications. Auckland Pioneer was developed for multi-destination trip planning and integrates real-time public transport services with search functions for places of interest. A test trial was conducted in Auckland, New Zealand, and the findings show the effects of the application on multidestination trip planning in comparison to traditional information sources such as GoogleTransit. This research contributes to existing literature by demonstrating the importance of personalized information en-route for user multi-destination trip planning. With information to assist trip planning and provide step-by-step guidance en-route, users tend to feel more confident to ride public transport.

Understanding factors influencing public transport passengers’ pre-travel information-seeking behaviour

“…A European study on options for supporting the development of Cooperative Intelligent Transport Systems (C-ITS) suggests that the deployment of personalised ITS sub-systems (using smartphones and personalised navigation devices like Tomtom) could have immediate benefits (Asselin-Miller et al 2016). Investigation of the use of smart mobile devices for journey planning is timely, as other research has shown that smartphone-based real-time information reduces the actual and perceived wait times experienced by transit riders (Watkins et al 2011;Chowdhury and Giacaman 2015); and can assist with trips in unfamiliar areas (Chowdhury and Giacaman 2015). There are also emerging studies on the use of smart card data for bus arrival time computation enhancement (Zhou et al 2017), and for understanding passenger-to-rail assignment and crowding cost to develop business cases and inform pricing policies (Hörcher et al 2017).…”

Smart Public Transport: A Bi-Objective Model for Maximizing Synchronizations and Minimizing Costs in Bus Timetables

“…For every line h in the system, Constraint (10) schedules-at least-the minimum number of trips required to statistically prevent congestion. Constraints (11) and (12) impose the time interval between two consecutive trips of the same bus line (i.e., the headway) to fall within the predefined boundaries of Hd min h and Hd max h , respectively. Similarly, Constraint (13) enforces that the first trip of each bus line h ∈ H in the planning horizon, i.e., x h 1 , departs in the interval [0, Hd max h ].…”

“…Achieving synchronization of multi-leg (transfer) trips is a critical aspect of the timetabling problem. Synchronization implies ensuring that passengers that have to combine different modes of transport (e.g., different bus lines) to reach their destination have sufficient time to alight from one mode of transport and board the other mode of transport in intermediate stops [12]. Among the diverse modes of transport, the synchronization of timetables of bus lines is widely recognized as a highly complex problem in public transport [13][14][15].…”

A Multi-Criteria Evaluation of Applications Supporting Public Transport Users

“…For some time now, there has been growing interest among researchers in studying the development and usability of mobile travel applications tools [26][27][28][29][30][31][32][33][34][35][36][37]. The various journey planner solutions have a number of different attributes (functionalities), which translate into less information for the traveller to use.…”